Evidence map›Paper›PMID 33654398›Full record

ReviewInternational journal of nanomedicine2021

Nanosized Drug Delivery Systems for Breast Cancer Stem Cell Targeting.

Li Lv, Yonghui Shi, Junyan Wu, Guocheng Li

Abstract readReview
In one paragraph

Review in International journal of nanomedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Li LvDepartment of Pharmacy, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, Guangdong, People's Republic of China.
Yonghui ShiDepartment of Pharmacy, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, Guangdong, People's Republic of China.
Junyan WuDepartment of Pharmacy, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, Guangdong, People's Republic of China.
Guocheng LiDepartment of Pharmacy, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, Guangdong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer stem cells (BCSCs), also known as breast cancer initiating cells, are reported to be responsible for the initiation, progression, therapeutic resistance, and relapse of breast cancer. Conventional therapeutic agents mainly kill the bulk of breast tumor cells and fail to eliminate BCSCs, even enhancing the fraction of BCSCs in breast tumors sometimes. Therefore, it is essential to develop specific and effective methods of eliminating BCSCs that will enhance the efficacy of killing breast tumor cells and thereby, increase the survival rates and quality of life of breast cancer patients. Despite the availability of an increasing number of anti-BCSC agents, their clinical translations are hindered by many issues, such as instability, low bioavailability, and off-target effects. Nanosized drug delivery systems (NDDSs) have the potential to overcome the drawbacks of anti-BCSC agents by providing site-specific delivery and enhancing of the stability and bioavailability of the delivered agents. In this review, we first briefly introduce the strategies and agents used against BCSCs and then highlight the mechanism of action and therapeutic efficacy of several state-of-the-art NDDSs that can be used to treat breast cancer by eliminating BCSCs.

Indexed as

Drug Delivery SystemsParticle SizeBreast NeoplasmsFemaleHumansNanoparticlesNeoplastic Stem CellsSignal TransductionBCSCsbreast cancer stem cellsnanosized drug delivery systemsNDDSssignaling pathwaysurface markerstarget

Identifiers

PMID33654398
PMCPMC7914063

What Socratic holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.